Getting the Most From Supply Chain Analytics

Because a company’s supply chain is typically complex—though able to significantly affect cost structures and profits—it is ripe for the insights that analytics can unearth.

That’s according to a recent article from Deloitte Consulting that notes multiple industries can improve forecasts, demand planning, sourcing, and production by infusing analytics into the supply chain.

“Companies with leading supply chain capabilities have typically made significant shifts in their use of advanced analytics to transform historical data captured in Enterprise Resource Planning systems into predictive insights,” notes Jerry O’Dwyer, Deloitte Consulting principal for U.S. Sourcing and Procurement. “These companies are using advanced analytics on every aspect of their supply chain.”

For example, in the retail sector, investing in analytics can mean eliminating inefficiencies in large and small companies. For example, the article points to a retail chain that used enterprise-wide analytics to discover that it had stores only miles apart that were using separate processes to procure everything from landscape maintenance services to large capital equipment, while at the same time paying two significantly different prices for building materials from the same supplier.

“Since retailers are in the retail business, not the analytics business, they may be reluctant to step outside that core competency,” adds Brian Umbenhauer, principal at Deloitte. “But investing in analytics can actually free them to focus on what they do best, because it can identify more efficient ways to handle peripheral activities. Every procurement decision has a total cost of ownership that can benefit from a closer look, whether it’s part of merchandise planning or an indirect cost of doing business.”

Companies in the manufacturing sector can realize margin improvements from two to four percent by applying more analysis to the data they already have, the article points out.

Savings can come from a variety of ways, including:

Reducing over payment for parts. “On average, up to one-third of the parts a manufacturer procures will be ‘new’ each year, but they differ only in small, specific ways from earlier versions,” according to Sanjay Agarwal, principal at Deloitte. “A company with good modeling ability can identify these discrete parameters of change and use them to determine what the net price change should be.”

Avoiding commodities volatility. Because the cost of raw materials fluctuates, analytics can be used to predict where prices will go so firms can then use options, futures, and contract provisions to prepare for cost changes.

Boosting merger and acquisition efficiency. When companies merge, they might be acquiring the same parts or materials, but may have different labeling mechanisms or prices.

“If each legacy company continues to use its own internal part numbers, that disparity can persist long after a merger,” Agarwal concluded. “Analytics can use Original Equipment Manufacturing product codes to unmask redundancies so that buyers can rationalize their procurement and save money.”